Ou baselines use recent ideas from contrastive learning [1]}, [2]}, [3]}, [4]}, [5]}, [6]}, [7]}, [8]} where representations are learned by discriminating between specific instances in a dataset.
In particular, we adapt four algorithms from computer vision to speech: Instance Discrimination or IR [1]}, Local Aggregation or LA [2]}, Momentum Contrast or MoCo [5]}, and SimCLR [6]}.
One of our contributions is to establish comparable baselines for audio representation learning.
As a close relative, we also evaluate representations learned using Wav2Vec-1.0 [13]} and Wav2Vec-2.0 [14]}.
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